Defining the resilience of the human salivary microbiota by a 520-day longitudinal study in a confined environment: the Mars500 mission

Supragingival microbiota, cytokines, and proteins in individuals with different trajectories in experimental gingivitis

Background

Gingivitis in response to biofilm formation may exhibit different trajectories. The purposes of the present study were to characterize the composition of the supragingival microbiota and salivary cytokine and protein levels in healthy individuals with different gingivitis patterns, to test the hypothesis that manifestations of gingivitis associate with specific profiles in terms of supragingival microbiota, salivary cytokines, and proteins.

Methods

Forty orally and systemically healthy individuals refrained from all oral hygiene procedures for a period of 14 days, followed by a resolution period of 14 days with regular oral care. Supragingival plaque level and bleeding on probing (BOP) were recorded, and supragingival plaque as well as saliva samples were collected at baseline, day 14, and day 28. Based on change in BOP% from baseline to day 14, rapid (n = 15), moderate (n = 10), and slow (n = 15) responders were identified. Supragingival microbiota composition, salivary cytokine, and protein levels were compared between groups at baseline, day 14, and day 28.

Results

A significantly higher baseline abundance of Capnocytophaga, Eikenella, and Campylobacter species were recorded in rapid responders, whereas a significantly higher baseline abundance of Streptococcus species were detected in slow responders. Slow responders expressed a high degree of resilience, with minimal difference in microbial composition at baseline and after 14 days of resolution (day 28). On the contrary, significant differences in relative abundance of members of the core microbiota, Streptococcus, Actinomyces, and Rothia species, was noted in baseline samples versus day 28 samples in rapid responders. Comparable baseline cytokine and protein levels were recorded in all groups.

Conclusion

Supragingival microbiota composition, but not saliva cytokine and protein profiles, seems to influence the extent of the inflammatory response during development of gingivitis in systemically healthy individuals.

Cross-regulation of antibody responses against the SARS-CoV-2 Spike protein and commensal microbiota via molecular mimicry

The commensal microflora provides a repertoire of antigens that illicit mucosal antibodies. In some cases, these antibodies can cross-react with host proteins, inducing autoimmunity, or with other microbial antigens. We demonstrate that the oral microbiota can induce salivary anti-SARS-CoV-2 Spike IgG antibodies via molecular mimicry. Anti-Spike IgG antibodies in the saliva correlated with enhanced abundance of Streptococcus salivarius 1 month after anti-SARS-CoV-2 vaccination. Several human commensal bacteria, including S. salivarius, were recognized by SARS-CoV-2-neutralizing monoclonal antibodies and induced cross-reactive anti-Spike antibodies in mice, facilitating SARS-CoV-2 clearance. A specific S. salivarius protein, RSSL-01370, contains regions with homology to the Spike receptor-binding domain, and immunization of mice with RSSL-01370 elicited anti-Spike IgG antibodies in the serum. Additionally, oral S. salivarius supplementation enhanced salivary anti-Spike antibodies in vaccinated individuals. Altogether, these data show that distinct species of the human microbiota can express molecular mimics of SARS-CoV-2 Spike protein, potentially enhancing protective immunity.

Participants in the Trans-Antarctic Winter Traverse Expedition Showed Increased Bacterial Load and Diversity in Saliva but Maintained Individual Differences within Stool Microbiota and Across Metabolite Fingerprints

Understanding the impact of long-term physiological and environmental stress on the human microbiota and metabolome may be important for the success of space flight. This work is logistically difficult and has a limited number of available participants. Terrestrial analogies present important opportunities to understand changes in the microbiota and metabolome and how this may impact participant health and fitness. Here, we present work from one such analogy: the Transarctic Winter Traverse expedition, which we believe is the first assessment of the microbiota and metabolome from different bodily locations during prolonged environmental and physiological stress. Bacterial load and diversity were significantly higher during the expedition when compared with baseline levels (p < 0.001) in saliva but not stool, and only a single operational taxonomic unit assigned to the Ruminococcaceae family shows significantly altered levels in stool (p < 0.001). Metabolite fingerprints show the maintenance of individual differences across saliva, stool, and plasma samples when analysed using flow infusion electrospray mass spectrometry and Fourier transform infrared spectroscopy. Significant activity-associated changes in terms of both bacterial diversity and load are seen in saliva but not in stool, and participant differences in metabolite fingerprints persist across all three sample types.

Integrating bioinformatic strategies in spatial life science research

As space exploration programs progress, manned space missions will become more frequent and farther away from Earth, putting a greater emphasis on astronaut health. Through the collaborative efforts of researchers from various countries, the effect of the space environment factors on living systems is gradually being uncovered. Although a large number of interconnected research findings have been produced, their connection seems to be confused, and many unknown effects are left to be discovered. Simultaneously, several valuable data resources have emerged, accumulating data measuring biological effects in space that can be used to further investigate the unknown biological adaptations. In this review, the previous findings and their correlations are sorted out to facilitate the understanding of biological adaptations to space and the design of countermeasures. The biological effect measurement methods/data types are also organized to provide references for experimental design and data analysis. To aid deeper exploration of the data resources, we summarized common characteristics of the data generated from longitudinal experiments, outlined challenges or caveats in data analysis and provided corresponding solutions by recommending bioinformatics strategies and available models/tools.

Effects of Long-Term Enclosed Environment on Human Health Based on the Analysis of Salivary Microbiota and Cytokines

The long-term exposure to enclosed environments may lead to chronic stress in crewmembers and affect their physical and mental state. Salivary microbiome and biomarkers of immune function are increasingly used in human health research. The "Lunar Palace 365" project, which was a 370-day, multicrew, enclosed experiment carried out in a ground-based bioregenerative life support system platform named Lunar Palace 1 (LP1). We investigated the temporal dynamics of the salivary microbiota and cytokines in the third phase of the "Lunar Palace 365" experiment, including 1 month before entering LP1 and 1 month after leaving Lp1. Results reveal no regular temporal change pattern in these parameters (highly abundant phyla and genera) during the experiment. Although the crewmembers' oral microbiota temporally changed, it recovered quickly after the study subjects left the enclosed environment. The levels of IL-6, IL-10, and TNF-α in crewmembers' saliva decreased after leaving the normal environment for the enclosed environment, indicating that their oral inflammatory response level was reduced. There were significant individual differences in crewmembers' salivary microbiota, however, the shared living space reduced these differences. Moreover, air microbiota might have also played a significant role in reducing the individual differences. In summary, the enclosed environment did not result in persistent changes in human salivary microbiota and oral immunity. This study provides some insights for studying the effect of enclosed controlled environments on human immunity and microbiome. IMPORTANCE Long-term exposure to space environments may influence the human microbiome, the human immune system, and the intricate balance between the two, causing impaired immunity and increased disease susceptibility. It was previously believed that the main potential factors of long-term spaceflight on human health were microgravity and radiation. However, the effects of long-term enclosed environments on human health were unclear. Bioregenerative life support systems (BLSS) is a good experimental model for studying the effects of enclosed environments on human systemic microbiota and immune disorders. We monitored the microbiota and cytokines in the saliva of crewmembers before they entered BLSS, during their stay in BLSS, and after leaving BLSS. The results indicated long-term closed environment will not cause persistent changes in human salivary microbiota and immunity.

Site- and Time-Dependent Compositional Shifts in Oral Microbiota Communities

Objectives

The oral microbiota plays a significant role in oral health. The present study aims to characterize variations in the oral microbiota relative to the collection site, the dynamics of biofilm accumulation, and inherent inter-individual differences.

Methods

Whole stimulated saliva and tooth biofilm samples from the 16 defined tooth regions were collected after 1, 2, or 3 days without oral hygiene (accumulation time) in six healthy adults with no signs of active caries or periodontal disease. The routines and conditions before and between sample collections were carefully standardized. Genomic DNA was extracted, and the V3-V4 regions of the 16S rRNA gene were amplified by PCR and sequenced on an Illumina MiSeq platform. Sequences were quality controlled, amplicon sequence variants (ASVs) were clustered, and taxonomic allocation was performed against the expanded Human Oral Microbiome Database (eHOMD). Microbial community profiles were analyzed by multivariate modeling and a linear discriminant analysis (LDA) effect size (LEfSe) method.

Results

The overall species profile in saliva and tooth biofilm differed between participants, as well as sample type, with a significantly higher diversity in tooth biofilm samples than saliva. On average, 45% of the detected species were shared between the two sample types. The microbiota profile changed from the most anterior to the most posterior tooth regions regardless of whether sampling was done after 1, 2, or 3 days without oral hygiene. Increasing accumulation time led to higher numbers of detected species in both the saliva and region-specific tooth biofilm niches.

Conclusion

The present study confirms that the differences between individuals dominate over sample type and the time abstaining from oral hygiene for oral microbiota shaping. Therefore, a standardized accumulation time may be less important for some research questions aiming at separating individuals. Furthermore, the amount of DNA is sufficient if at least two teeth are sampled for microbiota characterization, which allows a site-specific characterization of, for example, caries or periodontitis.